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20172022
most citedA Fast and Robust BERT-based Dialogue State Tracker for Schema-Guided Dialogue Dataset

10 citations · 24 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CL2022

Shallow Fusion of Weighted Finite-State Transducer and Language Model for Text Normalization

Evelina Bakhturina, Yang Zhang, Boris Ginsburg

Text normalization (TN) systems in production are largely rule-based using weighted finite-state transducers (WFST). However, WFST-based systems struggle with ambiguous input when…

cs.CL20217 cited

A Unified Transformer-based Framework for Duplex Text Normalization

Tuan Manh Lai, Yang Zhang, Evelina Bakhturina +2

Text normalization (TN) and inverse text normalization (ITN) are essential preprocessing and postprocessing steps for text-to-speech synthesis and automatic speech recognition, res…

cs.CL20214 cited

SGD-QA: Fast Schema-Guided Dialogue State Tracking for Unseen Services

Yang Zhang, Vahid Noroozi, Evelina Bakhturina +1

Dialogue state tracking is an essential part of goal-oriented dialogue systems, while most of these state tracking models often fail to handle unseen services. In this paper, we pr…

cs.CL20212 cited

NeMo Inverse Text Normalization: From Development To Production

Yang Zhang, Evelina Bakhturina, Kyle Gorman +1

Inverse text normalization (ITN) converts spoken-domain automatic speech recognition (ASR) output into written-domain text to improve the readability of the ASR output. Many state-…

cs.CL2020

BioMegatron: Larger Biomedical Domain Language Model

Hoo-Chang Shin, Yang Zhang, Evelina Bakhturina +4

There has been an influx of biomedical domain-specific language models, showing language models pre-trained on biomedical text perform better on biomedical domain benchmarks than t…

cs.CL20171 cited

Sentiment Classification using Images and Label Embeddings

Laura Graesser, Abhinav Gupta, Lakshay Sharma +1

In this project we analysed how much semantic information images carry, and how much value image data can add to sentiment analysis of the text associated with the images. To bette…